1. Field of the Invention
The present invention relates to a machine learning device, a motor control system, and a machine learning method for learning the cleaning interval of a fan motor.
2. Description of the Related Art
Conventionally, machines such as NC (Numerical Control) machine tools and robots are equipped with electric motors (driving motors), and fan motors are generally provided to dissipate heat released from such driving motors.
Since NC machine tools, robots, and the like are used in, e.g., factories having various dust particles, dirt adheres to or dust accumulates in, e.g., fan motors and air vents, thus lowering the cooling capacities of driving motors. Therefore, the users of machines such as NC machine tools, robots, and the like may preferably clean fan motors and air vents (“to clean fan motors and air vents” will also be referred to as “to clean fan motors” hereinafter).
When the cooling capacity of a fan motor declines, this raises the temperature of the driving motor and especially the temperature of the grease in the bearings of the driving motor. The life of the motor is considerably related to the life of the grease in the bearings and the life of the grease is significantly influenced by temperature. In other words, the life of the grease is known to shorten with increased temperature and, for example, the life of the grease may shorten by several tens of thousands of hours when the temperature of the grease increases only by about 10° C.
Conventionally, Japanese Laid-open Patent Publication No. 2005-249277 (Patent Document 1), for example, proposes a technique for conducting maintenance works on fans (fan motors) at optimal timings.
As described above, for example, the users of machines such as NC machine tools, robots, and the like may preferably clean fan motors (clean fan motors and air vents), and the cleaning intervals of the fan motors (the cleaning timings of the fan motors) are determined on the basis of empirical rules, including the technique disclosed in Patent Document 1.
For example, Patent Document 1 discloses determining that a maintenance period has come when the difference between the initial characteristics of the total preferable airflow volume vs. fan rotational speed stored in an initial characteristic storage unit and the actual characteristics obtained from a characteristic correction/update unit falls outside a predetermined range. Even in this case, however, the predetermined range for the difference between the initial characteristics of the fan (fan motor) and the actual characteristics is determined depending on empirical rules.
When the fan motor is too seldom cleaned, for example, the temperature of the driving motor rises and the life of the driving motor (or the machine including the driving motor) reduces. When the fan motor is cleaned too frequently, for example, the operating ratio of the machine lowers and the productivity, in turn, lowers.
In consideration of the above-described problem, it is an object of the present invention to provide a machine learning device, a motor control system, and a machine learning method which can improve both the life of an electric motor and the operating ratio of a machine.